We are seeking a highly experienced Senior Architect specializing in Agentic AI and Machine Learning to design, guide, and govern scalable Machine Learning solutions using Azure Machine Learning.
Position Overview
Experience: 12–16 years
Work Model: Hybrid
Shift: Day shift
Required Skills: Machine Learning, Azure, Azure Machine Learning
Preferred Domain Experience: Distributed Order Management
Technology: Custom Service
Role Classification: Senior Architect – Technology [45TC00]
Required Certification: Microsoft Certified: Azure AI Engineer Associate or an equivalent cloud certification focused on Machine Learning
Key Responsibilities
- Define end-to-end Machine Learning solution architectures aligned with enterprise standards, leveraging Azure Machine Learning services to deliver reliable, reusable components that can scale with business growth.
- Design data pipelines and feature engineering workflows to prepare high-quality training and inference datasets, integrating structured and unstructured data from multiple enterprise systems.
- Implement robust MLOps practices in Azure Machine Learning, automating model training, validation, deployment, and monitoring to ensure consistent performance and rapid iteration cycles.
- Partner closely with Data Scientists, Data Engineers, and application teams to transition experimental models into secure, efficient, production-ready services that meet latency, accuracy, and resiliency requirements.
- Establish standards and guardrails for model governance, including versioning, audit readiness, ethical-use considerations, and ongoing risk assessment across Machine Learning solutions.
- Optimize compute, storage, and networking choices within Azure Machine Learning to balance performance, reliability, sustainability, and cost efficiency for batch and real-time workloads.
- Guide teams on best practices for experimentation, feature utilization, model explainability, and drift detection to improve trust and transparency for business stakeholders.
- Document reference architectures, technical decision records, and reusable blueprints that enable project teams to accelerate new Machine Learning initiatives while maintaining architectural consistency.
- Partner with Product Owners and Business Analysts to translate strategic objectives into Machine Learning roadmaps that prioritize high-value use cases and measurable business outcomes.
- Evaluate emerging Azure Machine Learning capabilities and open-source frameworks, conduct structured proofs of concept, and recommend adoption paths that provide clear long-term value.
- Coordinate the integration of Machine Learning services with enterprise applications, APIs, and event streams to create seamless intelligent workflows that improve user and customer experiences.
- Assess non-functional requirements, including security, privacy, scalability, observability, and operational resiliency, and define repeatable standards for Machine Learning solutions.
- Mentor senior technical contributors in areas such as model industrialization, cloud-native design, and data-driven solution architecture to improve overall delivery quality across programs.
Qualifications
- Extensive hands-on experience architecting and delivering Machine Learning solutions using Azure Machine Learning, including data preparation, model training, deployment, and monitoring.
- Strong knowledge of Python-based Machine Learning ecosystems and cloud-native design patterns, with the ability to define architectures that support both experimentation and reliable production services.
- Experience with distributed systems or Distributed Order Management domains, designing intelligent solutions capable of handling large-scale order flows, inventory signals, and fulfillment constraints.
- Deep understanding of data modeling, data quality management, and feature engineering to ensure models are built on reliable and trusted data foundations.
- Proven experience working in hybrid work models and cross-functional Agile environments, effectively coordinating with geographically distributed stakeholders.
- Strong ability to analyze complex business problems, identify Machine Learning opportunities, and clearly communicate architectural recommendations to both technical and non-technical audiences.
Required Certification
Microsoft Certified: Azure AI Engineer Associate or an equivalent cloud certification focused on Machine Learning.